Papers
8,340 papers found
Optimal Convergence Rates for Agnostic Nyström Kernel Learning
Jian Li, Yong Liu, Weiping Wang
Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning
Tongzhou Wang, Antonio Torralba, Phillip Isola et al.
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs
Junkai Zhang, Weitong Zhang, Quanquan Gu
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits
Jongyeong Lee, Junya Honda, Chao-Kai Chiang et al.
Optimally-weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference
Ayush Bharti, Masha Naslidnyk, Oscar Key et al.
Optimal No-Regret Learning for One-Sided Lipschitz Functions
Paul Duetting, Guru Guruganesh, Jon Schneider et al.
Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits
Heyang Zhao, Dongruo Zhou, Jiafan He et al.
Optimal randomized multilevel Monte Carlo for repeatedly nested expectations
Yasa Syed, Guanyang Wang
Optimal Rates and Efficient Algorithms for Online Bayesian Persuasion
Martino Bernasconi, Matteo Castiglioni, Andrea Celli et al.
Optimal Sets and Solution Paths of ReLU Networks
Aaron Mishkin, Mert Pilanci
Optimal Shrinkage for Distributed Second-Order Optimization
Fangzhao Zhang, Mert Pilanci
Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion
Ashok Cutkosky, Harsh Mehta, Francesco Orabona
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization
Sijia Chen, Wei-Wei Tu, Peng Zhao et al.
Optimistic Planning by Regularized Dynamic Programming
Antoine Moulin, Gergely Neu
Optimization for Amortized Inverse Problems
Tianci Liu, Tong Yang, Quan Zhang et al.
Optimizing DDPM Sampling with Shortcut Fine-Tuning
Ying Fan, Kangwook Lee
Optimizing Hyperparameters with Conformal Quantile Regression
David Salinas, Jacek Golebiowski, Aaron Klein et al.
Optimizing Mode Connectivity for Class Incremental Learning
Haitao Wen, Haoyang Cheng, Heqian Qiu et al.
Optimizing NOTEARS Objectives via Topological Swaps
Chang Deng, Kevin Bello, Bryon Aragam et al.
Optimizing the Collaboration Structure in Cross-Silo Federated Learning
Wenxuan Bao, Haohan Wang, Jun Wu et al.
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning
Matthias Gerstgrasser, David C. Parkes
Orthogonality-Enforced Latent Space in Autoencoders: An Approach to Learning Disentangled Representations
Jaehoon Cha, Jeyan Thiyagalingam
Oscillation-free Quantization for Low-bit Vision Transformers
Shih-Yang Liu, Zechun Liu, Kwang-Ting Cheng
Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation
Wenqing Zheng, S P Sharan, Ajay Kumar Jaiswal et al.